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Increasing population density and mobility contribute to the high incidence of the acute respiratory viral infections and the emergence of dangerous epidemic situations associated with them The XXI century began with an epidemic (November 1, 2002 - July 31, 2003) caused by the coronavirus of Severe Acute Respiratory Syndrome (SARS-CoV) (Coronaviridae, Betacoronavirus);this was later followed by a pandemic was registered in 2009 (June 11, 2009-August 10, 2010) of the so-called Swine Influenza (H1N1) pdm09 (Orthomyxoviridae, influenzavirus A);in 2012, the Middle East Respiratory Syndrome coronavirus (MERS - COV) (Coronaviridae, Betacoronavirus) showed its epidemic potential December 2019 was the month of the beginning of epidemic of the modern COVID-19 (Coronavirus Disease 2019), etiologically related to SARSCoV-2 (temporarily named 2019-nCoV - 2019 novel coronavirus) March 11, 2020 World health organization has announced the beginning of the COVID-19 pandemic The modern paradigm of mass differential diagnosis of acute respiratory diseases is based on the indication of the pathogen using polymerase chain reaction (PCR), but this, firstly, does not exclude the establishment of a preliminary differential diagnosis based on clinical data, and secondly, differential clinical diagnosis comes to the fore during major epidemic outbreaks (especially in developing countries), the scale of which exceeds the practical possibilities of laboratory diagnostics This is the reason why diagnostic decision-making support systems are one of the most promising areas of digitalization in the medical practice This paper presents the results of the development of a medical diagnostic service that is based on a model of medical knowledge and an intelligent decision-maker The model of medical knowledge, in turn, includes models of definitions, medical diagnosis, medical history, and justification of the decisions made An intelligent decision-maker generates a structured report using common medical definitions about diseases that have either been confirmed or rejected by the system, and a detailed justification of the decisions made The developed cloud service allows users to accumulate data on the clinical manifestations of acute respiratory viral infections and to use artificial intelligence methods to generate solutions that can significantly facilitate and speed up the establishment of the preliminary diagnosis
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